Balancing flexibility and security in Europe? The impact of unemployment on young peoples’ subjective well-being

Abstract

We examine the relationship between ‘flexicurity’ systems, unemployment and well-being outcomes for young people in Europe. A key tenet of the flexicurity approach is that greater flexibility of labour supply supports transitions into employment, trading longer-term employment stability for short-term job instability. However, there is a risk that young people experience greater job insecurity, both objective and subjective, with less stable contracts and more frequent unemployment spells. Our research draws on data from the European Social Survey and uses multi-level models to explore whether and how flexibility-security arrangements moderate the effect of past and present unemployment on the well-being of young people. We distinguish between flexibility-security institutions that foster improved job prospects and those that provide financial security.

Keywords

Europe flexicurity labour market institutions life satisfaction subjective well-being unemployment youth

Introduction

The impact of labour market regulation on overall performance and the integration of labour market participants has preoccupied policy-makers and researchers for many years (Freeman, 2005). A key issue has been balancing the security needs of participants with pressures for flexibility. These debates and concerns have driven much policy-making in Europe. As new labour market entrants with frequent unstable contracts, young people are more likely to experience periods of unemployment and less likely to have adequate contribution histories to benefit from income security (Madsen et al., 2013). Considerable literature demonstrates that both insecure work and the insecurities of not having work can have negative effects on psychological well-being and physical health, including for young people (Bell and Blanchflower, 2011).

The promotion of ‘flexicurity’ policies by Denmark and the Netherlands, and subsequently by the European Commission (2007) was seen as an attempt to redress the imbalance of flexibility and security policies (European Commission, 2007; Wilthagen and Tros, 2004). Although young people were not central to the drive for flexicurity policy, they had much to gain, at least in principle, from addressing the gap between ‘insiders’ and ‘outsiders’ and enhancing security for those most likely to experience unstable employment. The concept and original application relied heavily on the combination of flexible contracts and labour market institutions providing income security and support for rapid and well-matched re-entry into employment through active labour market policy (ALMP) (Viebrock and Clasen, 2009). However, in many European countries there was a greater focus on the flexibility measures, including weaker employment protection legislation (EPL), with less attention to the security aspect (Burroni and Keune, 2011). Furthermore, the crisis and its disproportionate effects on youth and non-standard workers, who were the first to lose their jobs, put the concept under pressure and exposed the weaknesses identified by earlier authors (Heyes, 2011). Perhaps as a result, though also because of other changes in EU policy-making, the concept was quietly dropped (Smith et al., 2019). Nevertheless, the key principles of the European Pillar of Social Rights are inspired by flexicurity principles, with an important focus on income security. Moreover, the tension between demands for flexibility and security remain central to the subjective and objective experience of labour market participants and their overall well-being, in particular of young people (Smith et al., 2019).

While unemployment spells are common for young people in Europe, the experience of labour market insecurity is influenced by the institutional context. It is important to examine how flexicurity arrangements can moderate the effect of past and present unemployment experience on subjective well-being among young people. We use multi-level models to analyse whether the impact of unemployment on well-being (life satisfaction) is better explained by institutions and policies that foster greater job prospects or those that increase financial security. We use individual-level data on 20 countries from the 2004 and 2010 rounds of the European Social Survey (ESS, 2004, 2010); these contained special modules on work, family and well-being and include a wider range of variables relating to job conditions, including perceived security, employability and subjective well-being. We combine these with country-level information on institutions and policies, drawing on OECD sources among others. The ESS provides cross-national data with information on family and social supports, measures of perceived insecurity and outcome measures such as life satisfaction. We define youth as those between 15 and 34, in order to take into account early-career insecurity which is still be prevalent in the early 30s (O’Reilly et al., 2019). In order to capture potential heterogeneity in life satisfaction among young people, our models control for different age groups.

Below, we explore the literature around well-being of those with insecure labour market statuses and particularly the unemployed, focusing on research relating to young people and the institutional arrangements for flexibility and security. Then, we focus on methods, concepts and measurement, before presenting multi-level models of the impact of past and present unemployment on the subjective well-being of young people compared with older workers, and how it is affected by institutions and flexibility-security policies. Finally, we discuss the results of our analysis and draw out the implications for young people and labour market policies that seek to balance flexibility and security.

Literature

Considerable research demonstrates the consequences of unstable employment on physical and psychological health and well-being. These tend to focus either on unemployment (Bell and Blanchflower, 2011) or on job insecurity (De Witte, 2005; Virtanen et al., 2005). A few studies deal with the consequences of both unemployment and job insecurity on well-being and health (Gebel and Voßemer, 2014; Voßemer et al., 2018). However, the analysis of the impact of unstable employment on young people, particularly across institutional settings, is less developed. Here, we exclusively focus on studies that focus on unemployment, as these reflect best the approach we adopt.

Research on the link between unemployment and mental well-being dates back to the 1930s. A number of meta-analyses of the psychological literature confirm not only the negative consequences of job loss for psychological well-being but also a strong positive boost upon re-entering employment (McKee-Ryan et al., 2005; Paul and Moser, 2009). The negative effects of unemployment extend beyond the pecuniary impact, though there is a continuing debate on the relative influence of financial and non-financial factors, such as stigma and loss of meaningful activity (Latif, 2010; Nordenmark and Strandh, 1999).

Many of the studies observe differences in the strength of the relationship between unemployment and well-being, based on the characteristics of the unemployed person, such as gender, social class, age and family status (Nordenmark and Strandh, 1999). Several have found that the psychological impact of unemployment is greatest for prime-age workers, while younger workers and those approaching retirement age suffer less (Latif, 2010; Theodossiou, 1998). However, this finding is not universal (McKee-Ryan et al., 2005). Some attribute the weaker psychological impact of unemployment among young people to lower employment commitment (Carle, 1987; Jackson et al., 1983), while alternative explanations relate to the greater financial and family commitments of prime-age workers (Jackson and Warr, 1984).

Gebel and Voßemer (2014), drawing on the German Socio-Economic Panel and looking at both unemployment and objective job insecurity, found that unemployment, compared with temporary employment, is still the greater threat to psychological health. Voßemer et al. (2018), using ESS data, show that labour market policies are important in shaping the experience of unemployment but less relevant for workers in insecure jobs (fixed-term or no contract).

The potential effects of unemployment and job insecurity on well-being may not be limited to current experience. A scarring effect of past unemployment (in the previous 5 years) on current well-being was found by Clark et al. (2001), while Bell and Blanchflower (2011) find that spells of early-career unemployment are associated with lower life satisfaction, poorer health and reduced job satisfaction. Furthermore, these authors show that the overall levels of happiness among young people fall as aggregate levels of unemployment rise, so the effects are not limited to those currently unemployed.

For unemployment, there is a growing body of research that investigates whether the prevailing unemployment rate or economic situation in a country influences individual experiences. One hypothesis is that higher unemployment rates moderate the negative impact of unemployment by normalizing the experience, reducing expectations and reducing individual stigma (Clark, 2003). Alternatively, high unemployment may aggravate distress by depleting the level of support in wider social networks and reducing optimism about the future (Gallie and Russell, 1998). To date, the empirical results on the effects of the unemployment level on the well-being of the unemployed are mixed (Clark, 2003; Oesch and Lipps, 2013; Russell et al., 2013).

Voßemer et al. (2018) and Wulfgramm (2014), though not directly inspired by the flexicurity concept, focus explicitly on the moderating role of institutions on unemployment and well-being. Using ESS data, Wulfgramm (2014) finds that the generosity of unemployment benefits moderates the negative effect of unemployment on life satisfaction, whereas the positive moderating effect of ALMP turns out to be less robust. Voßemer et al. (2018) also find that more generous unemployment benefits buffer the negative effects of unemployment on well-being and they find that higher ALMP expenditures are associated with more negative effects of unemployment on well-being. The authors also found that reducing EPL for temporary contracts increased the negative effect of unemployment on well-being but not for regular contracts. Eichhorn (2014) based on European Values Study (EVS) data, in contrast, finds no significant moderating effect of the generosity of unemployment benefits on life satisfaction. The meta-analysis by Paul and Moser (2009) shows, however, that the negative effects of unemployment on mental health are lower with unemployment protection, stronger economic development and lower levels of income inequality. Overall, the results of these institutional approaches are inconsistent and there is a limited focus on youth. Burchell (2009) argues that an implicit assumption of ‘flexicurity’ is that job insecurity is no longer such a source of anxiety even though the correlation between insecurity and stress was no lower in countries seen as exemplars of flexicurity. He argued that flexicurity does not ameliorate non-financial costs of unemployment.

Drawing upon these studies, we aim to extend previous analyses in order to examine age differences and to apply additional institutional and macro-indicators in line with the flexicurity framework.

Methods, concepts and measurement

Our analysis uses the 2004 and 2010 rounds of the ESS, which covered the issues on which we focus. The sample is limited to 20 countries present in both waves (Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland and UK). Using two waves allows us to include two observations per country for the macro effects in the multivariate models. We focus on both the active and inactive population aged between 15 and 64 years. Our case numbers are 21,130 for youth (15–34 years) and 37,356 for adults (35–64 years).

The data comprise individuals clustered within countries, and therefore standard models that do not account for this clustering lead to biased estimates. The observations are also nested within years. Schmidt-Catran and Fairbrother (2016) have demonstrated that ignoring the time level leads to downwards estimates of standard errors and we therefore specify clusters at three levels: country, year and country/year. We use random intercept multi-level models, which allow us to estimate both individual-level and institutional-level effects for the flexicurity arrangements.

Measures of well-being and individual-level explanatory variables

We adopt a measure of life satisfaction, our dependent variable, based on responses to the question: ‘All things considered, how satisfied are you with your life nowadays?’ This was measured on an 11-point scale from 0 (extremely dissatisfied) to 10 (extremely satisfied). We prefer this to the World Health Organization well-being measure, since it provides greater societal-level variance and is widely used in the literature (Clark and Oswald, 1996; Diener and Suh, 1997; Russell et al., 2013; Wulfgramm, 2014)

Average well-being among employed youths, ranges from around six points in Greece to more than eight points in Denmark (see Supplemental Figure A1). Among the unemployed, Hungary has the lowest rating with under five points and Slovenia and Norway the highest, around 7.5 points. Except for Slovenia where no difference appears, satisfaction is higher among young employed than unemployed. We might imagine that unemployed youth in countries with more encompassing passive and ALMP will display well-being effects closer to those of employed youth. However, at first glance, there is no evident link between ‘flexicurity regime’ and overall life satisfaction outcomes across unemployed and employed persons. The difference between both groups is smallest in Norway, Greece and Portugal and is also relatively small in the Netherlands, Switzerland, the UK and Poland. Differences are largest in Sweden, Hungary and Slovakia (see Supplemental Material for full results). These findings indicate that we have to go beyond welfare state institutions in our models to identify factors that might generate resilience and increase well-being.

Regarding individual-level explanatory variables, our main interest is the impact of employment stability and the role of financial support from other household members. In addition to current employment status (employed, unemployed and out of the labour market), we include a separate indicator of past unemployment experience in the previous 5 years, with only spells of unemployment of 3 months or more recorded. We expect that financial support from other household members would act as functional equivalent to institutional income security and thus moderate this effect. To test this, we include a measure of financial hardship in the household, identifying those who find it difficult or very difficult to cope on their current income. We also ran the models without the financial hardship measure (see Supplemental Material) and also test the effect of institutional supports without this control. Based on the previous literature, we include a range of control variables found to influence subjective well-being including gender, age, education, self-defined health, household type, children, marital status, social support and frequency of socializing (see Supplemental Table A1 for detailed definitions).

The role of institutions in well-being: the flexibility-security framework and the macro-level variables

Our choice of macro-level variables is inspired by the flexicurity concept, which maintains that the right combination of different forms of flexibility and security will lead to better employment prospects and greater individual well-being. Some approaches, particularly those based on the Danish model, have stressed the benefit of combining labour market flexibility, reliable unemployment benefits and participation in ALMP – the ‘golden triangle’ (Madsen et al., 2013). Similarly, the European flexicurity strategy pointed to several elements that can contribute to smoother transitions between jobs: flexible contractual arrangements, lifelong learning, ALMP and modern social security systems (European Commission, 2007). This implies a shift from job security to employment security or employability and increased emphasis on financial security during transitions such as unemployment.

We propose a range of institutional variables related to the main dimensions of the flexibility-security nexus: job security/labour market flexibility, employment security/employability and income security (see Table 1). Whereas the first two indicators capture employment prospects, the third reflects financial security in unemployment. While the flexicurity concept stresses the importance of the right combinations of flexibility and security, our analysis can only capture these combinations to a limited degree.

Table 1.

Macro-level institutions and policy measures and their link to the flexicurity framework.

Employment prospects		Financial security
(1) Job security/labour market flexibility	(2) Employment security/employability	(3) Income security
EPL indicators for regular and temporary workers Perceived insecurity (percentage of employees feeling very insecure)	ALMP expenditure/unemployed (percentage of GDP) Participant stocks in ALMP (percentage of labour force) Average unemployment over 5 years (youth and total)	Passive labour market policy (PLMP) (expenditure/unemployed as % of GDP)

Source: OECD, ESS, LFS.

See Supplemental Table A2 for country scores for both time periods.

For the job security/labour market flexibility dimension, we include EPL indicators (OECD, 2013), which measure separately the strictness of regulation of individual dismissal of employees on permanent contracts and regulations on the use of fixed-term contracts and temporary agency work (TAW). Evidence on the impact of EPL on employment and unemployment is inconclusive (OECD, 2004), and the indicators have been criticized for their methodology and for exclusion of employment protection achieved by collective bargaining (Deakin et al., 2007; ILO, 2012). More recent versions resolve some issues (OECD, 2013; Venn, 2009). However, Myant and Brandhuber (2016) highlight several remaining shortcomings, and Maleszyk (2016) points to exemptions targeted at groups such as apprentices and enforced protection for others such as pregnant women. We therefore test an alternative measure capturing employees’ perceived feelings of labour market insecurity derived on the country level from the ESS data; we focus on those employed feeling very insecure. This indicator provides a direct sense of how (in)secure employees feel; it thus provides a subjective measure of job (in)security and labour market flexibility.

The second dimension captures employment security or employability, since transitions between jobs can be facilitated and improved qualitatively by enhancing employability. This usually results from participation in ALMP or lifelong learning. Our indicator is expenditure on ALMP as percentage of GDP relative to the level of unemployment and average country-level unemployment over 5 years. (Alternatives such as lagged year-to-year change in unemployment rates led to very similar results.) Both are standard measures (Chung and van Oorschot, 2011). As a complementary measure, we also include participation in ALMP. It could be that given lower eligibility to unemployment benefits, youth will be disadvantaged relative to adults in access to ALMP, if programmes are administered in connection with passive benefits. On the other hand, recent reforms have seen a strong linkage between benefit receipt and activation of youth (Leschke and Finn, 2019). We know of no comparative indicator that captures ALMP targeted at youth only.

Our third dimension covers income security. We use PLMP expenditure related to the level of unemployment, as a percentage of GDP. Arguably, this indicator captures both benefit coverage and generosity. Given the more limited access of youth to unemployment benefits, we would have liked to include a more direct measure of benefit coverage, but there are a number of problems with the available data (Van Oorschot, 2013). The unemployment benefit coverage data provided by Scruggs et al. (2014) are unsuitable for the young, as they only contain less accessible unemployment insurance benefits and use long contribution histories. For our purpose, the best indicator would be the unemployment benefit coverage indicator from the EU Labour Force Survey (LFS), which has lately become available (Maquet et al., 2016). However, it does not provide information for Ireland, the Netherlands and Norway.

Finally, we include trade union density as a contextual factor, responding to criticism of an overemphasis on EPL to the detriment of wider labour market structures (Ibsen and Mailand, 2010) and to emphasize the role of social partners in labour market regulation, which has been seen as one of the characteristics of flexicurity exemplars (Viebrock and Clasen, 2009). Supplemental Table A2 provides the full information on the macro-indicators for each country in 2004 and 2010.

Model results

Individual-level predictors of life satisfaction

In the first model, we examine the individual-level effects on life satisfaction (Table 2). We include both current unemployment status and, separately, recent experience of unemployment in order to capture ‘scarring’ influences on well-being. The reference group consists of those currently employed, and for our retrospective measure, those who have not experienced a spell of unemployment of 3 months or more in the preceding 5 years. Our discussion focuses on the individual-level effects for people aged under 35; however, the results for those aged 35–64 are provided in Table 2 for comparison.

Table 2.

Random intercept multi-level models of life satisfaction (scored 0–10): individual effects.

	Under 35	35–64
(Easily) coping on present income
Difficult/very difficult to cope	−0.861***	−1.243***
Current status (reference: employed)
Unemployed	−0.504***	−0.385***
Inactive	0.178***	−0.065**
No unemployment in past 5 years
Unemployment in past 5 years	−0.350***	−0.382***
Female	0.0445*	0.158***
Health good/very good
Health fair/bad/very bad	−0.828***	−0.789***
Age (years) (reference: 30–34)
15–19	0.508***
20–24	0.215***
25–29	0.128***
Age (years) (reference: 35–54)
55–64		0.249***
Social support
Frequently socialize	0.170***	0.133***
Someone for support	0.548***	0.551***
Reference: not living with parents
Living with one parent	−0.157***	−0.066
Living with two parents	0.045	0.001
Reference: no children
Child(ren) under 18	0.024	0.069***
Reference: single never married
Living with partner	0.477***	0.391***
Widowed	−1.215***	−0.057
Separated/divorced	−0.165*	−0.170***
Reference: higher education
Less than lower secondary	−0.157***	−0.107***
Lower secondary	−0.184***	−0.057*
Upper secondary	−0.144***	−0.086***
Post secondary	−0.129*	−0.089*
Constant	6.057***	6.030***
Variance components
Variance (country)	0.116	0.307
Variance (year)	0.003	0.002
Variance (country-year)	0.045	0.089
Variance individual	3.120	3.451
Individuals	21,130	37,356
Countries	20	20
Country years^a	39	39

France in the year 2004 drops out when we include ‘coping on present income’.

***

p < 0.01; **p < 0.05; *p < 0.1.

Among young Europeans, life satisfaction is highest among those who are economically inactive (including students), followed by the employed. Those with recent unemployment experience have lower satisfaction levels than those with none. The models control for household financial difficulty, which suggests that the unemployment effect, both past and present, has a significant non-financial dimension.¹ Financial hardship is one of the strongest predictors of life satisfaction for young people, reducing this by almost one point on an 11-point scale.

Availability of social support has been shown to be a key component of well-being and a moderator of stressful life events (Hall and Lamont, 2009). We find that more frequent contact with friends or family plus the availability of a close confidante are significantly associated with enhanced life satisfaction.

There is a small difference by gender in favour of women. The age coefficients suggest that the younger age groups have significantly higher levels of satisfaction compared with those aged 30–34 years with satisfaction decreasing with age.

The impact of co-residence with two parents is positive but not statistically significant, whereas young people living with a lone parent have significantly lower satisfaction than those living independently. As we control for financial difficulty this may be due to the increased psychological distress and work–family conflict among lone parents (Bianchi and Milkie, 2010).

Having children does not influence life satisfaction among the under 35s, living with a partner is associated with higher satisfaction but those who were previously married and are now divorced, separated or widowed have significantly lower satisfaction scores. Given these results, we cannot rule out that both material and non-material family resources act as functional equivalents to institutional support.

Institutional-level effects

We test a range of institutional country-level variables that reflect the aspects of the flexibility/security nexus. We first examine the influence of each variable separately (Table 3, Models A and C) before testing the simultaneous effects for a sub-set of variables (Models B and D). We then estimate models to test the cross-level interactions between institutional characteristics and individual employment status (Table 4). To facilitate comparison of the different institutional effects, we have rescaled all institutional variables to zero or one. The coefficients therefore represent the difference between those in the country/year where the value of the variable is lowest and those where it is highest.

Table 3.

Institutional and labour market influences on life satisfaction.

	Under 35		35–64
	ASeparate models	BJointly estimated	CSeparate models	DJointly estimated
Individual-level controls	√Coeff.	√Coeff.	√Coeff.	√Coeff.
Job security/flexibility
Employment protection regular contracts	−0.199*		−0.350**
Employment protection temporary contracts	−0.011		−0.181^a
Percentage of employed very insecure	−2.432***	−0.769**	−3.44***	−1.031**
Employment security/employability
ALMP spending (% GDP)^b	3.836***	0.630	6.363***	1.148 *
Participants in ALMP (percentage of lab force)	0.034		0.061
Average youth unemployment 5 years	−0.022*		−0.038**
Average total unemployment 5 years	−0.038**		−0.060**
Income security
Passive spending % GDP^c	1.358**	0.047	2.247***	0.128
Contextual
Union density	0.011***		0.175**

The results in columns A and C are taken from multiple models in which each institutional variable is separately evaluated. In Models B and D, the institutional variables are added simultaneously; the full models for B and D are available in the Supplemental Material. Models include all individual-level controls.

The model including EPL for temporary contracts for the 35- to 64-age group would not converge until the variable for financial difficulty was dropped.

Lagged by 1 year.

Spending adjusted by unemployment level.

***

p < 0.01; **p < 0.05; *p < 0.1.

Table 4.

Cross-level interactions: individual employment status and institutional factors, under 35 years.

	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6	Model 7
Individual level
Currently unemployed	−0.716***	−0.696***	−0.507***	−0.342***	−0.338***	−0.442***	−0.428***
Current OLM	0.0436	0.0866*	0.0814*	0.303***	0.303***	0.133***	0.324***
Unemployed in past 5 years	−0.425***	−0.409***	−0.397***	−0.329***	−0.318***	−0.418***	−0.392***
Control variables^a	√	√	√	√	√	√	√
Country level × Individual employment status
EPL regular contracts^b	−0.875**
Unemployment × EPL regular	0.365***
OLM × EPL regular	0.567***
Past unemployment × EPL regular	0.207
EPL temporary contracts^b		−0.216
Unemployment × EPL temporary contracts		0.245**
OLM × EPL temporary contracts		0.470***
Past unemployment × EPL temporary		0.155
Unemployment rate 5 year average^b			−0.730***
Unemployment × Unemployment rate			0.308***
OLM × unemployment rate			0.0163
Past unemployment × unemployment rate			0.146
PLMP^b				0.931***
Unemployment × PLMP				−0.472***
OLM × PLMP				−0.667***
Past unemployment × PLMP				−0.0812
ALMP^b					1.253***
Unemployment × ALMP					−0.460***
OLM × ALMP					−0.705***
Past unemployment × ALMP					−0.131
% feel insecure						−1.156***
Unemployment × % feel insecure						0.153
OLM × % feel insecure						−0.194
Past unemployment × %feel insecure						0.234*
Union density^b							0.922***
Unemployment × union density							−0.241
OLM × union density							−0.438***
Past unemployment × union density							0.141
Constant	6.380***	6.142***	6.290***	5.815***	5.713***	6.384***	5.741***
N	21,130	21,130	21,130	21,130	21,130	21,130	21,130

Models include all individual-level controls shown in Table 2.

The main effect for the institutional variable is the effect for the employed who are the reference group.

***

p < 0.01; **p < 0.05; *p < 0.1.

We first examine indicators of the job security/labour market flexibility dimension. Stricter regulation of individual dismissal of employees with regular contracts (a reflection of lower flexibility) is only weakly associated with youth well-being, and contrary to segmentation theory, this negative effect is stronger for over 35s, and only significant (negative) for the young employed (cross-level interactions Table 4, Model 1).² This effect may be driven by employed young people with insecure contracts, given the association between strong EPL for regular contracts and the proportion of youth on fixed-term contracts.

The strictness of regulations on the use of fixed-term contracts and TAW has no effect on young people’s well-being overall, nor does this vary by current/past employment status (Table 4, Model 2 and Supplemental Material). The effect is not significant for older adults, including in the cross-level interactions by employment status (Supplemental Material). These results suggest that EPL as currently measured has relatively little influence on the life satisfaction of young people.

In contrast to the weak influence of EPL indicators, the proportion of those in employment who feel very insecure is consistently and more strongly associated with lower life satisfaction; this effect holds for both youth and adults. There is no significant interaction with current personal employment status (Table 4, Model 6).

The second set of measures relate to employment security or employability. This encompasses measures of the national rate of unemployment and investment in ALMP. Higher ALMP spending and lower rates of unemployment are significantly and positively associated with life satisfaction for young people and for those aged over 35. The cross-level interactions show that the positive association between well-being and ALMP is stronger for those in employment than for those unemployed or inactive (Table 4, Model 5), a pattern also found by Voßemer et al. (2018).³ Activation policies involving greater monitoring and sanctions may counteract some of the positive well-being effects. The proportion of the labour force in ALMP has no influence on life satisfaction.

There is a very small reduction in life satisfaction associated with higher unemployment rates, less than 0.05 difference on an 11-point scale between those with the highest and lowest unemployment rates. This effect is somewhat weaker but still statistically significant for young people who are unemployed compared with those in employment (Table 4, Model 3) in line with the buffering hypothesis, but the effect is too small to be meaningful,⁴ suggesting the individual experience of unemployment that has the dominant effect on well-being rather than wider societal levels.

Income security as measured by spending on unemployment benefits (adjusted by the unemployment rate) has a positive influence on life satisfaction for youth and a somewhat higher influence for adults. Living in the country/year with the most generous welfare is associated with an increase of 1.4 in young people’s life satisfaction scores relative to those in the least generous context. The cross-level interactions point to a weaker effect on youth currently unemployed compared with employed youth (Table 4, Model 4) and further tests show that the PLMP effect for unemployed youth is insignificant (see Supplemental Material), whereas for those aged over 35 the effect does not differ by current or past employment status. This may arise in the case of younger unemployed since few are covered by such income supports (Leschke and Finn, 2019). Moreover, the influence of the welfare system is to some degree already working through the indicator of financial difficulty at the individual level. As noted above, the coefficient for unemployment is significantly reduced when financial difficulty is included. For this reason, we also ran the models without the financial difficulty controlled (see Supplemental Material); both the negative effect of current unemployment increases and the positive coefficient for PLMP spending increase as anticipated. This shows that the PLMP effect is partially mediated through reduced financial stress. However, the pattern of the interactions with individual unemployment remains the same in that the positive effect of PLMP is greater for the employed group than for young people unemployed or outside the labour market.

Finally, union density as an important contextual variable capturing representation and an additional source of security at the workplace has a small positive association with life satisfaction for those under 35 and a stronger association for those over 35 (Table 3) as might be suggested by variation in union density by age (Vandaele, 2019).

In Models B and D (Table 3), we enter the institutional-level variables simultaneously. This corresponds with institutional complementarities at the heart of flexicurity. Given the small number of cases at the second level, there is a risk of over-specifying the model; we therefore select one variable to represent each policy dimension, that with the strongest association with well-being when introduced separately in the models. The results suggest that for young people the flexibility measure, as captured by perceived insecurity among workers at the societal level, had the strongest (negative) influence on life satisfaction.

In contrast, the employability dimension as captured by ALMP expenditure per unemployed plays a positive role at the societal level for life satisfaction. However, this effect is stronger for those aged over 35 than youth. The effect of ALMP for youth becomes insignificant when unemployment benefits are also included. When included simultaneously with other institutions, spending on unemployment benefits becomes insignificant for both age groups. Nevertheless, the strong role of financial difficulty at the individual level (see full set of results for Model B and D in the Supplemental Material) means that income security is important for life satisfaction.⁵

A model without any controls demonstrates 6 percent of variance in life satisfaction among young adults occurs at the country level, and a further 2 percent at the country-year level. Under 1 percent of variance is explained by the year. The remainder of the variance occurs at the individual level. This is higher for adults aged 35–64 years (14 and 4 percent, respectively). The individual controls introduced in the first model (Table 2), explain 15 percent of variance at the individual level, 55 percent of the country-level variation and 39 percent of the country-year variation. This means that over half of the original differences between countries can be explained by variation in the characteristics of the individuals within each country. Even when controlling for individual characteristics there is more variation at the country and country/year level for older workers (6 as against 3 percent) suggesting societal factors have a stronger influence for this age group.

For young people, adding the three institutional variables explains an additional 25 percent of variance in well-being at the country level, 19 percent at the country-year level and 2 percent of total variance (the figures for over 35s are 21, 23 and 3 percent, respectively). Therefore, while there is more variation at country level among older workers even when controlling for composition, these three institutional characteristics combined have a similar impact for both age groups. It seems therefore that other institutions may be more influential for older than younger workers.

Discussion and conclusion

We have explored whether flexicurity arrangements moderate the effect of unemployment on subjective well-being among young people, a group not considered in previous studies. A focus on employed and unemployed youth is appropriate, as they have higher unemployment rates and are more likely to experience employment insecurity. While young adults report higher levels of satisfaction than older adults, the gap in satisfaction between employed and unemployed youth for the sample as whole is at least as wide as for older adults. There are important variations across countries in the satisfaction of employed and unemployed youth but in aggregate, this variation does not seem to be linked to ‘flexicurity regimes’. These results indicate that we have to go beyond welfare state institutions in our analyses and examine the household context, and in particular material and non-material support by family and social networks that might generate resilience.

With regard to the institutional analysis, we assess a range of alternative measures capturing the flexibility-security interface. As regards job security/labour market flexibility, we went beyond the commonly used (but often criticized) EPL indicators by including a subjective measure of job insecurity derived from the ESS data. To capture employment security/employability, we took into account both unemployment rates and measures relating to ALMP. We demonstrate that it is important to consider the strength of industrial relations as a contextual factor, and our results support studies that find a positive impact of trade union density on well-being.

Our results show that institutions at the flexibility-security interface matter, but that individual-level factors, and in particular family resources, are more important. Institutions, according to our models, matter more for older adults than for youth, which may be explained by youth having lower access to unemployment benefits and often to AMLP, and lower protection associated with an over-representation in temporary positions. The results imply that support deriving from family or other social networks might act as a functional equivalent to institutions and policies for flexibility-security. On the other hand, we find little variation in well-being by gender among young people. However, it is likely that individual-level factors, especially those relating to family structure including the age of children, might vary across young men and women.

While overall well-being is higher among youth than adults, and institutions seem to matter more for adults than youth, we found similarities in terms of direction of effects for young people and adults across the models including the effects on institutions. Employment protection institutions as captured by conventional indicators have little influence on well-being of youth. However, subjective insecurity across the workforce as a whole is associated with lower life satisfaction regardless of current employment status, for both youth and adults.

At the country level, we find a strong significant effect for ALMP expenditure when included alone; it has a stronger impact on the employed than unemployed or inactive (though the effect is still positive for both groups). This pattern was also found by Voßemer et al. (2018) and may be associated with the conditionality and sanctions attached to supports to the unemployed in high-ALMP countries. The ALMP effect for youth becomes insignificant when included with expenditure on unemployment benefits and subjective insecurity levels.

We find a small positive effect for income security (passive expenditure per unemployed) when included alone. The larger effect for older adults reflects that income security policies cater less to youth because of required contribution histories and means-testing which can adversely affect those still living at home with parents. In line with the findings on ALMP expenditure, the effect on PLMP is more positive for those employed and non-significant for unemployed and inactive youth. In fact, we find no effect on income security for either youth or older adults when controlling for subjective insecurity levels and ALMP expenditure per unemployed. At the same, time our models controlling for financial hardship at the individual level show an important positive role of income security at the individual level and a strong positive impact of living with a partner. Here, we see signs of welfare at the household level acting as functional equivalents of weak welfare state provision.

Overall, our results have implications for the analysis of the role of institutions for labour market outcomes among particular sub-groups, namely young people. First, flexicurity presupposes the combination of policies that foster flexibility and security, yet data availability means that we cannot test these outcomes directly. Second, institutional measures that distinguish directly between youth and adults are frequently unavailable and thus limit analyses. Third, in spite of some recent developments the institutional variables are still insufficient regarding the income-dimension of flexicurity, for example in relation to unemployment benefits. Given the poor state of available measures and the limitations of cross-sectional data, we assess youth-sensitive institutional variables by using different specifications and alternative measures. Given the centrality of labour market policy at the flexibility-security interface to well-being outcomes, adequate measures and thus analysis are essential. It is important that institutional measures applicable to diverse population groups – young and old, men and women – are enhanced to improve the analysis of policy measures and subsequent labour market processes and outcomes for the whole population.

Supplemental Material

Russell_et_al._online_suppl – Supplemental material for Balancing flexibility and security in Europe? The impact of unemployment on young peoples’ subjective well-being

Supplemental material, Russell_et_al._online_suppl for Balancing flexibility and security in Europe? The impact of unemployment on young peoples’ subjective well-being by Helen Russell, Janine Leschke and Mark Smith in European Journal of Industrial Relations

Footnotes

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This article has benefited from funding from the European Union’s Seventh Framework Programme for Research, Technological Development and Demonstration under Grant Agreement no. 613256 ().

Supplemental material

Supplemental material for this article is available online.

Notes

Author biographies

Helen Russell is Research Professor at the Economic and Social Research Institute in Dublin and Adjunct Professor of Sociology at Trinity College Dublin.

Janine Leschke is Professor with special responsibilities in Comparative Labour Market Analysis at the Department of International Economics, Government and Business at Copenhagen Business School.

Mark Smith is Professor of Human Resource Management at Grenoble Ecole de Management, Univ Grenoble Alpes ComUE.

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